Accelerate your design and simulation processes with our Machine Learning models
Our Mission
Empower your design, CAD, and simulation engineering teams to accelerate product development cycles by 100x while maximizing product performance.
Are your physics based simulations (FEM, CFD) slowing down product development?
Tired of computationally and time-intensive simulations?
Let us take the burden off your shoulders, leave the heavy lifting to us
Revolutionize your engineering with OptiNeura AI
OptiNeura AI provides an advanced platform that accelerates simulation and design processes by leveraging your Computer-Aided Engineering datasets
New stardard for Simulation Predictions
Our models allow you to visualize the impact of your new design in few seconds
Instant Design Recommendations
Our platform offers immediate suggestions to enhance your design, eliminating the need for lengthy iterative optimizations
Our Mantra: Stay hungry, stay foolish
Our Crew of Innovators
Alex Donzelli
Cofounder & CEO
He is a Caltech's trained engineer and business developer with expertise in physics-based simulations. He launched his career by designing and building simulation models for diverse industries.
His early professional experience includes roles as a Simulation and Product Development Engineer at Saipem, one of the largest multinational oilfield services companies, and at Optotune, a Zurich-based startup specializing in manufacturing optical devices for the machine vision industry.
To complement his engineering background, he expanded his expertise into business strategy and management consulting within the financial services sector at UBS, where he led multi-million dollar projects.
During his academic tenure, he contributed to developing a transmission component for the automated measurement and quality control of Porsche Electric Axles.
He holds a Master’s degree in Applied Mechanics from the California Institute of Technology, where he specialized in Computational Mechanics. As a Researcher at Caltech, he developed virtual-experiment frameworks that significantly reduced R&D costs and timelines by integrating Finite Element simulations with optical algorithms. This project resulted in several publications in peer-reviewed journals, including Experimental Mechanics.
Jan-Hendrik Bastek
Cofounder & CTO
He is a distinguished researcher specializing in deep learning frameworks for engineering applications. His doctoral research at ETH Zurich and Columbia University introduced cutting-edge machine learning methods that advanced the design and analysis of engineering materials, with publications in top journals like PNAS and Nature Machine Intelligence.
One of his most notable projects demonstrated that generative AI can design metamaterials with complex mechanical properties, impacting fields from aerospace to biomedical engineering. He has also developed expertise in physics-based modeling, including physics-informed neural networks and integrating physical equations into generative frameworks.
He earned a Master’s degree in Mechanical Engineering from ETH Zurich, where he was awarded the prestigious ETH Medal for his thesis on viscoelastic truss metamaterials. He also holds a Bachelor's degree in Industrial Engineering from Technische Universität Braunschweig, supported by a German National Academic Foundation scholarship. His diverse research spans projects from analyzing regional economic inequalities using satellite data to studying diamond wire sawing for silicon wafer manufacturing.
Beyond academia, he has applied his skills in consulting and engineering. At Boston Consulting Group, he provided strategic advice for the MedTech and insurance sectors, and he gained engineering experience at Volkswagen AG in Wolfsburg, Germany, and Progress-Werk Oberkirch AG in Suzhou, China.
Are you a high-energy individual with:
- Experience developing and applying 3D deep learning frameworks and optimization techniques,
- Proficiency in Python,
- A solid understanding of Physics,
We want you in our team!
Must have:
- Motivation to accelerate the R&D cycles of hardware-based products,
- Feeling compelled to simplify the work of Engineers and Researchers,
- Excitement about making an impact across multiple engineering industries (incl. Energy, Aerospace, Automotive, Medical, Semiconductors),
- Relentlessness and willingness to roll up your sleeves.
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